arXiv (All)
open access
Beyond the Illusion of Power: Calibrating Quasi-Experiments in Observational IS
Information systems (IS) researchers increasingly use quasi-experimental methods such as difference-in-differences (DiD) and instrumental variables (IV) to recover causal effects from observational panel data. Power calculations that justify these designs assume i.i.d. errors, but the deeper problem
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Experimental effects and causal representations#744542
- Estimating Heterogeneous Causal Effects with Tree-Based Methods under Imperfect Compliance#1115725
- Differential Data Protection Regimes in Data-Driven Research: Why the GDPR is More Research-Friendly Than You Think#964628
- Debunking decreases mistaken causal inferences: A direct replication of Irving et al. (2022)#397123
- Explaining to laypeople why bootstrapping works#787250
Record · ID 1063510
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive